September 12, 2015
One page summary
- Vertical slice is completed
- All sub-systems are very simple
- No progress on ATLANTIS
The main ingredient
- A policy simulator makes sense only as long as the agents are adaptive
- Main decision: where do I go fishing?
- This is currently done in two ways:
- Multi-Logit Discrete Choice Models
- Dynamic Programming
Complications
- Maps are large!
- The biomass distribution is unknown
- The biomass distribution changes when interacted with
- Other agents interact with biomass at the same time
Adaptation two sub-problems
- Deciding where to fish involves two sub-problem:
- Search: how to find the "best" spot available
- Exploration/Exploitation: when to look for a "better" spot and when to stay where we currently are
A simple "crowbar" for adaptation
- Write once, use always
- Judge trips by their \(\frac {\Pi}{t}\)
- 80% of the time explore, 20% of the time exploit
- When exploiting, fish at the seatile that has been most profitable so far
- When exploring, fish at a random seatile neighboring the best one you know
A simple problem

Finding the right spot
With a little help
- We can create a social network linking fishers
- They can exchange information about the best spot
- When "exploiting" a fisher can go to his own best spot or to the one of his best friends.
A simple run
Oil Prices
Fish the line (part 1)
Fish the line (part 2)
By-catch (part 1)
By-catch (part 2)
No heuristic is best

Friends can be useless (part 1)

Friends can be useless (part 2)

The scientific feedback loops
- Simulation suggests heuristic algorithm
Interviews test it
- Interviews suggest heuristic algorithm
Simulation tests it
Changing Gear

Changing Gear (part 2)

Effort, with very low prices

Effort, with very high prices

Emergent endogenous prices

The limits of feedback
- Trial and Error is versatile and can solve multiple problems at once
- Sometimes you can guess the error without trying
- Sometimes imitation is hard
Policy Simulation
ITQ Reservation Prices

TAC vs ITQ Different Gear

TAC vs ITQ Gas Efficiency

General objectives
- Expand ITQs to multiple species
- Ground model in realistic parameters
- Improve heuristics
- Deploy model internally